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To obtain insight into the motional features of proteins for enzymatic function, we studied binding reactions between ferredoxin-NADP(+) reductase (FNR) and ferredoxin (Fd) using isothermal titration calorimetry and NMR-based magnetic relaxation and hydrogen/deuterium exchange (HD(ex)). Fd-FNR binding was accompanied by endothermic reactions and driven by the entropy gain. Component-wise analysis of the net entropy change revealed that increases in the conformational entropy of the Fd-FNR complex contributed largely to stabilizing the complex. Intriguingly, analyses of magnetic relaxation and HD(ex) rates with X-ray B factor implied that Fd binding led to both structural stiffening and softening of FNR. Enhanced FNR backbone fluctuations suggest favorable contributions to the net conformational entropy. Fd-bound FNR further showed that relatively large-scale motions of the C terminus, a gatekeeper for interactions of NADP(+) (H), were quenched in the closed form, thereby facilitating exit of NADP(+) (H). This can provide a first dynamic structure-based explanation for the negative cooperativity between Fd and NADP(+) (H) via FNR., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

We used the orientation-dependent Optimized Side Chain Atomic eneRgy (OSCAR-o), derived in an early study, for protein loop selection. The prediction accuracy of OSCAR-o was better than that of physics-based force fields or statistical potential energy functions for both the RAPPER decoy set and the Jacobson decoy set. The native conformer was frequently ranked as lowest energy among the decoys. Furthermore, strong correlation was observed between the OSCAR-o score and the root mean square deviation (RMSD) from the native structure for energy-minimized decoys. In practical use, we applied OSCAR-o to rescore decoys generated by a widely used loop-modeling program, LOOPY. As a result, the mean RMSD values of top-ranked decoys were reduced by 0.3 Å for loop targets of seven to nine residues. We expect similar performance for OSCAR-o with other loop-modeling algorithms in the context of decoy rescoring. A loop selection program (OSCAR-ls) based on OSCAR-o is available at http://sysimm.ifrec.osaka-u.ac.jp/OSCAR/., (Copyright © 2011 Wiley-Liss, Inc.)

We describe the development of new force fields for protein side chain modeling called optimized side chain atomic energy (OSCAR). The distance-dependent energy functions (OSCAR-d) and side-chain dihedral angle potential energy functions were represented as power and Fourier series, respectively. The resulting 802 adjustable parameters were optimized by discriminating the native side chain conformations from non-native conformations, using a training set of 12,000 side chains for each residue type. In the course of optimization, for every residue, its side chain was replaced by varying rotamers, whereas conformations for all other residues were kept as they appeared in the crystal structure. Then, the OSCAR-d were multiplied by an orientation-dependent function to yield OSCAR-o. A total of 1087 parameters of the orientation-dependent energy functions (OSCAR-o) were optimized by maximizing the energy gap between the native conformation and subrotamers calculated as low energy by OSCAR-d. When OSCAR-o with optimized parameters were used to model side chain conformations simultaneously for 218 recently released protein structures, the prediction accuracies were 88.8% for χ(1) , 79.7% for χ(1 + 2) , 1.24 Å overall root mean square deviation (RMSD), and 0.62 Å RMSD for core residues, respectively, compared with the next-best performing side-chain modeling program which achieved 86.6% for χ(1) , 75.7% for χ(1 + 2) , 1.40 Å overall RMSD, and 0.86 Å RMSD for core residues, respectively. The continuous energy functions obtained in this study are suitable for gradient-based optimization techniques for protein structure refinement. A program with built-in OSCAR for protein side chain prediction is available for download at http://sysimm.ifrec.osaka-u.ac.jp/OSCAR/., (Copyright © 2011 Wiley Periodicals, Inc.)

Background: Regulation of gene expression, protein synthesis, replication and assembly of many viruses involve RNA-protein interactions. Although some successful computational tools have been reported to recognize RNA binding sites in proteins, the problem of specificity remains poorly investigated. After the nucleotide base composition, the dinucleotide is the smallest unit of RNA sequence information and many RNA-binding proteins simply bind to regions enriched in one dinucleotide. Interaction preferences of protein subsequences and dinucleotides can be inferred from protein-RNA complex structures, enabling a training-based prediction approach., Results: We analyzed basic statistics of amino acid-dinucleotide contacts in protein-RNA complexes and found their pairing preferences could be identified. Using a standard approach to represent protein subsequences by their evolutionary profile, we trained neural networks to predict multiclass target vectors corresponding to 16 possible contacting dinucleotide subsequences. In the cross-validation experiments, the accuracies of the optimum network, measured as areas under the curve (AUC) of the receiver operating characteristic (ROC) graphs, were in the range of 65-80%., Conclusions: Dinucleotide-specific contact predictions have also been extended to the prediction of interacting protein and RNA fragment pairs, which shows the applicability of this method to predict targets of RNA-binding proteins. A web server predicting the 16-dimensional contact probability matrix directly from a user-defined protein sequence was implemented and made available at: http://tardis.nibio.go.jp/netasa/srcpred.

An enhanced conformational sampling method, multicanonical molecular dynamics (McMD), was applied to the ab intio folding of the 57-residue first repeat of human glutamyl- prolyl-tRNA synthetase (EPRS-R1) in explicit solvent. The simulation started from a fully extended structure of EPRS-R1 and did not utilize prior structural knowledge. A canonical ensemble, which is a conformational ensemble thermodynamically probable at an arbitrary temperature, was constructed by reweighting the sampled structures. Conformational clusters were obtained from the canonical ensemble at 300 K, and the largest cluster (i.e., the lowest free-energy cluster), which contained 34% of the structures in the ensemble, was characterized by the highest similarity to the NMR structure relative to all alternative clusters. This lowest free-energy cluster included native-like structures composed of two anti-parallel α-helices. The canonical ensemble at 300 K also showed that a short Gly-containing segment, which adopts an α-helix in the native structure, has a tendency to be structurally disordered. Atomic-level analyses demonstrated clearly that inter-residue hydrophobic interactions drive the helix formation of the Gly-containing segment, and that increasing the hydrophobic contacts accompanies exclusion of water molecules from the vicinity of this segment. This study has shown, for the first time, that the free-energy landscape of a structurally well-ordered protein of about 60 residues is obtainable with an all atom model in explicit water without prior structural knowledge.

Background: Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively., Results: We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest., Conclusions: The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Background: In order to characterize mammalian intrinsically disordered domains (IDDs) we examined the patterns in their amino acid abundance as well as overrepresented local sequence motifs. We considered IDDs from mouse proteins associated with innate immune responses as well as a set of generic human genes. These sets were compared with artificially generated random sequences with the same overall amino acid abundance and length distributions. IDDs were then clustered by amino acid abundance, and further analyzed in terms of co-occurrence of clusters with functionally characterized Pfam domains., Results: Overall, IDDs were very different from randomly generated sequences. The deviation from random distributions was at least as great as that for ordered domains, for which the deviation can be rationalized in terms of strong evolutionary pressure for structure and function. The co-occurrence of certain Pfam domains with specific IDD clusters was found to be significant (p-value < 0.01). Local sequence motifs that were over-represented in the innate immune set consisted mostly of low complexity fragments, primarily characterized by amino acid repeats, and could not be assigned an obvious functional role., Conclusions: Our results suggest that IDDs are constrained within a narrow subset of possible sequences. This is most likely a result of biophysical restraints that have yet to be elucidated. More detailed examination of the functional relationship between the IDDs and associated Pfam domains is one possible avenue of investigation.

Polarization of macrophages to M1 or M2 cells is important for mounting responses against bacterial and helminth infections, respectively. Jumonji domain containing-3 (Jmjd3), a histone 3 Lys27 (H3K27) demethylase, has been implicated in the activation of macrophages. Here we show that Jmjd3 is essential for M2 macrophage polarization in response to helminth infection and chitin, though Jmjd3 is dispensable for M1 responses. Furthermore, Jmjd3 (also known as Kdm6b) is essential for proper bone marrow macrophage differentiation, and this function depends on demethylase activity of Jmjd3. Jmjd3 deficiency affected trimethylation of H3K27 in only a limited number of genes. Among them, we identified Irf4 as encoding a key transcription factor that controls M2 macrophage polarization. Collectively, these results show that Jmjd3-mediated H3K27 demethylation is crucial for regulating M2 macrophage development leading to anti-helminth host responses.

Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies.

Background: Accurate prediction of antigenic epitopes is important for immunologic research and medical applications, but it is still an open problem in bioinformatics. The case for discontinuous epitopes is even worse - currently there are only a few discontinuous epitope prediction servers available, though discontinuous peptides constitute the majority of all B-cell antigenic epitopes. The small number of structures for antigen-antibody complexes limits the development of reliable discontinuous epitope prediction methods and an unbiased benchmark to evaluate developed methods., Results: In this work, we present two novel server applications for discontinuous epitope prediction: EPSVR and EPMeta, where EPMeta is a meta server. EPSVR, EPMeta, and datasets are available at http://sysbio.unl.edu/services., Conclusion: The server application for discontinuous epitope prediction, EPSVR, uses a Support Vector Regression (SVR) method to integrate six scoring terms. Furthermore, we combined EPSVR with five existing epitope prediction servers to construct EPMeta. All methods were benchmarked by our curated independent test set, in which all antigens had no complex structures with the antibody, and their epitopes were identified by various biochemical experiments. The area under the receiver operating characteristic curve (AUC) of EPSVR was 0.597, higher than that of any other existing single server, and EPMeta had a better performance than any single server - with an AUC of 0.638, significantly higher than PEPITO and Disctope (p-value < 0.05).

Motivation: Functional similarity between proteins is evident at both the sequence and structure levels. SeSAW is a web-based program for identifying functionally or evolutionarily conserved motifs in protein structures by locating sequence and structural similarities, and quantifying these at the level of individual residues. Results can be visualized in 2D, as annotated alignments, or in 3D, as structural superpositions. An example is given for both an experimentally determined query structure and a homology model., Availability and Implementation: The web server is located at http://www.pdbj.org/SeSAW/.

Infection by Toxoplasma gondii down-regulates the host innate immune responses, such as proinflammatory cytokine production, in a Stat3-dependent manner. A forward genetic approach recently demonstrated that the type II strain fails to suppress immune responses because of a potential defect in a highly polymorphic parasite-derived kinase, ROP16. We generated ROP16-deficient type I parasites by reverse genetics and found a severe defect in parasite-induced Stat3 activation, culminating in enhanced production of interleukin (IL) 6 and IL-12 p40 in the infected macrophages. Furthermore, overexpression of ROP16 but not ROP18 in mammalian cells resulted in Stat3 phosphorylation and strong activation of Stat3-dependent promoters. In addition, kinase-inactive ROP16 failed to activate Stat3. Comparison of type I and type II ROP16 revealed that a single amino acid substitution in the kinase domain determined the strain difference in terms of Stat3 activation. Moreover, ROP16 bound Stat3 and directly induced phosphorylation of this transcription factor. These results formally establish an essential and direct requirement of ROP16 in parasite-induced Stat3 activation and the significance of a single amino acid replacement in the function of type II ROP16.

Monoamine oxidase membrane enzymes are responsible for the catalytic breakdown of extra- and intracellular neurotransmitters and are targets for the development of central nervous system drugs. We analyzed the dynamics of rat MAOA by performing multiple independent molecular dynamics simulations of membrane-bound and membrane-free forms to clarify the relationship between the mechanics of the enzyme and its function, with particular emphasis on the significance of membrane attachment. Principal component analysis of the simulation trajectories as well as correlations in the fluctuations of the residues pointed to the existence of three domains that define the global dynamics of the protein. Interdomain anticorrelated movements in the membrane-bound system facilitated the relaxation of interactions between residues surrounding the substrate cavity and induced conformational changes which expanded the active site cavity and opened putative pathways for substrate uptake and product release. Such events were less pronounced in the membrane-free system due to differences in the nature of the dominant modes of motion. The presence of the lipid environment is suggested to assist in decoupling the interdomain motions, consistent with the observed reduction in enzyme activity under membrane-free conditions. Our results are also in accordance with mutational analysis which shows that modifications of interdomain hinge residues decrease the activity of rat MAOA in solution.

Toll-like receptors (TLRs) recognize microbial components, and evoke inflammation and immune responses. TLR stimulation activates complex gene expression networks that regulate the magnitude and duration of the immune reaction. Here we identify the TLR-inducible gene Zc3h12a as an immune response modifier that has an essential role in preventing immune disorders. Zc3h12a-deficient mice suffered from severe anaemia, and most died within 12 weeks. Zc3h12a(-/-) mice also showed augmented serum immunoglobulin levels and autoantibody production, together with a greatly increased number of plasma cells, as well as infiltration of plasma cells to the lung. Most Zc3h12a(-/-) splenic T cells showed effector/memory characteristics and produced interferon-gamma in response to T-cell receptor stimulation. Macrophages from Zc3h12a(-/-) mice showed highly increased production of interleukin (IL)-6 and IL-12p40 (also known as IL12b), but not TNF, in response to TLR ligands. Although the activation of TLR signalling pathways was normal, Il6 messenger RNA decay was severely impaired in Zc3h12a(-/-) macrophages. Overexpression of Zc3h12a accelerated Il6 mRNA degradation via its 3'-untranslated region (UTR), and destabilized RNAs with 3'-UTRs for genes including Il6, Il12p40 and the calcitonin receptor gene Calcr. Zc3h12a contains a putative amino-terminal nuclease domain, and the expressed protein had RNase activity, consistent with a role in the decay of Il6 mRNA. Together, these results indicate that Zc3h12a is an essential RNase that prevents immune disorders by directly controlling the stability of a set of inflammatory genes.

A method to functionally annotate structural genomics targets, based on a novel structural alignment scoring function, is proposed. In the proposed score, position-specific scoring matrices are used to weight structurally aligned residue pairs to highlight evolutionarily conserved motifs. The functional form of the score is first optimized for discriminating domains belonging to the same Pfam family from domains belonging to different families but the same CATH or SCOP superfamily. In the optimization stage, we consider four standard weighting functions as well as our own, the "maximum substitution probability," and combinations of these functions. The optimized score achieves an area of 0.87 under the receiver-operating characteristic curve with respect to identifying Pfam families within a sequence-unique benchmark set of domain pairs. Confidence measures are then derived from the benchmark distribution of true-positive scores. The alignment method is next applied to the task of functionally annotating 230 query proteins released to the public as part of the Protein 3000 structural genomics project in Japan. Of these queries, 78 were found to align to templates with the same Pfam family as the query or had sequence identities > or = 30%. Another 49 queries were found to match more distantly related templates. Within this group, the template predicted by our method to be the closest functional relative was often not the most structurally similar. Several nontrivial cases are discussed in detail. Finally, 103 queries matched templates at the fold level, but not the family or superfamily level, and remain functionally uncharacterized., (2008 Wiley-Liss, Inc.)

The Protein Data Bank Japan (PDBj) curates, edits and distributes protein structural data as a member of the worldwide Protein Data Bank (wwPDB) and currently processes approximately 25-30% of all deposited data in the world. Structural information is enhanced by the addition of biological and biochemical functional data as well as experimental details extracted from the literature and other databases. Several applications have been developed at PDBj for structural biology and biomedical studies: (i) a Java-based molecular graphics viewer, jV; (ii) display of electron density maps for the evaluation of structure quality; (iii) an extensive database of molecular surfaces for functional sites, eF-site, as well as a search service for similar molecular surfaces, eF-seek; (iv) identification of sequence and structural neighbors; (v) a graphical user interface to all known protein folds with links to the above applications, Protein Globe. Recent examples are shown that highlight the utility of these tools in recognizing remote homologies between pairs of protein structures and in assigning putative biochemical functions to newly determined targets from structural genomics projects.

The anaerobic lifestyle of the intestinal parasite Blastocystis raises questions about the biochemistry and function of its mitochondria-like organelles. We have characterized the Blastocystis succinyl-CoA synthetase (SCS), a tricarboxylic acid cycle enzyme that conserves energy by substrate-level phosphorylation. We show that SCS localizes to the enigmatic Blastocystis organelles, indicating that these organelles might play a similar role in energy metabolism as classic mitochondria. Although analysis of residues inside the nucleotide-binding site suggests that Blastocystis SCS is GTP-specific, we demonstrate that it is ATP-specific. Homology modelling, followed by flexible docking and molecular dynamics simulations, indicates that while both ATP and GTP fit into the Blastocystis SCS active site, GTP is destabilized by electrostatic dipole interactions with Lys 42 and Lys 110, the side-chains of which lie outside the nucleotide-binding cavity. It has been proposed that residues in direct contact with the substrate determine nucleotide specificity in SCS. However, our results indicate that, in Blastocystis, an electrostatic gatekeeper controls which ligands can enter the binding site.

We have developed a new method to predict protein- protein complexes based on the shape complementarity of the molecular surfaces, along with sequence conservation obtained by evolutionary trace (ET) analysis. The docking is achieved by optimization of an object function that evaluates the degree of shape complementarity weighted by the conservation of the interacting residues. The optimization is carried out using a genetic algorithm in combination with Monte Carlo sampling. We applied this method to CAPRI targets and evaluated the performance systematically. Consequently, our method could achieve native-like predictions in several cases. In addition, we have analyzed the feasibility of the ET method for docking simulations, and found that the conservation information was useful only in a limited category of proteins (signal related proteins and enzymes)., ((c) 2007 Wiley-Liss, Inc.)

Background: Structure alignment methods offer the possibility of measuring distant evolutionary relationships between proteins that are not visible by sequence-based analysis. However, the question of how structural differences and similarities ought to be quantified in this regard remains open. In this study we construct a training set of sequence-unique CATH and SCOP domains, from which we develop a scoring function that can reliably identify domains with the same CATH topology and SCOP fold classification. The score is implemented in the ASH structure alignment package, for which the source code and a web service are freely available from the PDBj website http://www.pdbj.org/ASH/., Results: The new ASH score shows increased selectivity and sensitivity compared with values reported for several popular programs using the same test set of 4,298,905 structure pairs, yielding an area of .96 under the receiver operating characteristic (ROC) curve. In addition, weak sequence homologies between similar domains are revealed that could not be detected by BLAST sequence alignment. Also, a subset of domain pairs is identified that exhibit high similarity, even though their CATH and SCOP classification differs. Finally, we show that the ranking of alignment programs based solely on geometric measures depends on the choice of the quality measure., Conclusion: ASH shows high selectivity and sensitivity with regard to domain classification, an important step in defining distantly related protein sequence families. Moreover, the CPU cost per alignment is competitive with the fastest programs, making ASH a practical option for large-scale structure classification studies.

Plant type ferredoxin (Fd) is a small [2Fe-2S] cluster containing electron-transfer protein with a highly negative redox potential. Higher plants contain different iso-protein types of Fd in roots and leaves, reflecting the difference in redox cascades between these two tissues. We have combined subdomains of leaf and root Fds in recombinant chimeras, to examine structural effects and the relationship between groups of residues on redox potential, electron transfer, and protein-protein interactions. All chimeras had redox potentials that were intermediate to the wild type leaf and root Fds. Surprisingly, the largest differences resulted from exchange of the N-terminus, the region farthest from the redox center. Homology modeling and energy minimization calculations suggest that the N-terminal chimeras may indirectly influence redox potentials by structurally perturbing the active site. Measurements of electron transport and protein interaction indicate that synergistic interaction between the C- and N-terminal of root Fd bestows a specific high affinity for accepting electrons in the root type electron cascade, and that there is discrimination against photosynthetic electron donation to root Fd based on the C-terminus of the molecule. Taken together, the experimental and computational studies support a model in which higher order structure contributes to iso-protein specific interaction and electron-transfer properties.

Using an all-atom, molecular dynamics-based, flexible docking method, the tertiary and quaternary structures of protofilaments of the "K3" fragment from beta(2)-microglobulin (residues Ser20-Lys41) were predicted at low pH in a continuous mixture of water and 2,2,2-trifluoroethanol (TFE). Tetramers with energies very close to the global minimum were produced with C(alpha) root-mean square deviation values under 4A over 88 residues compared to a recently solved SSNMR structure. The most accurate model distinguishes itself from other low-energy solutions in that it shows high structural similarity to another known fold, the parallel beta-helix, in agreement with models proposed previously by several other groups. The method achieves efficiency without loss of generality or atomic detail by enforcing local symmetry on the individual peptides, rewarding intermolecular contacts, and iteratively building up the protofilaments by successively doubling the number of chains. Solvent effects were included in the model by treating the dielectric constant and surface tension as functions of the TFE concentration. In order to understand the physical basis for the stabilizing effects of TFE, the TFE concentration was varied from 0% to 50% (v/v) and a peak in stability was observed at 16%, where the polar and hydrophobic terms cancel out and close to the experimentally determined value of 20%.

The nature of military medical support necessarily changes in the transition from war fighting to the post-conflict phase. This paper examines the activity in the only British Military Hospital serving a multi-national divisional area in Iraq over 2004 during this post-conflict phase. Hand injuries were common and formed a large proportion of the workload seen at the military field hospital on operations. The overwhelming majority of hand trauma resulted in soft tissue injury. There was a clear predisposition to hand trauma for males, manual workers, combat soldiers and engineers/mechanics. While most hand injuries do not require surgical intervention, they impact on the effectiveness of the military population as a result of the large proportion of patients who are placed on restricted duties following hand trauma, 157 of 241 in this study, and the number of soldiers who require aeromedical evacuation for further treatment, 38 of 360 in this study. These injuries require that military surgeons and emergency physicians should be experienced in the initial management of hand trauma and hand trauma should be a core component of their training. The skills of the specialist hand surgeon may be required for definitive management of these injuries at a later stage.

Background: We introduce GASH, a new, publicly accessible program for structural alignment and superposition. Alignments are scored by the Number of Equivalent Residues (NER), a quantitative measure of structural similarity that can be applied to any structural alignment method. Multiple alignments are optimized by conjugate gradient maximization of the NER score within the genetic algorithm framework. Initial alignments are generated by the program Local ASH, and can be supplemented by alignments from any other program., Results: We compare GASH to DaliLite, CE, and to our earlier program Global ASH on a difficult test set consisting of 3,102 structure pairs, as well as a smaller set derived from the Fischer-Eisenberg set. The extent of alignment crossover, as well as the completeness of the initial set of alignments are examined. The quality of the superpositions is evaluated both by NER and by the number of aligned residues under three different RMSD cutoffs (2,4, and 6A). In addition to the numerical assessment, the alignments for several biologically related structural pairs are discussed in detail., Conclusion: Regardless of which criteria is used to judge the superposition accuracy, GASH achieves the best overall performance, followed by DaliLite, Global ASH, and CE. In terms of CPU usage, DaliLite CE and GASH perform similarly for query proteins under 500 residues, but for larger proteins DaliLite is faster than GASH or CE. Both an http interface and a simple object application protocol (SOAP) interface to the GASH program are available at http://www.pdbj.org/GASH/.

A new algorithm for superimposing protein structures based on maximizing the number of spatially equivalent residues is introduced. The algorithm works in three distinct steps. First, the optimal residue map is calculated by structural alignment. By default, the double dynamic programming algorithm, as implemented in the program ASH, was used for the structure alignment step, but we also present results based on alignments imported from three other programs (Dali, CE, and VAST).Second, the structures are spatially superimposed such that the effective number of equivalent residues (NER)--aligned residue pairs that can be spatially overlapped--is maximized. The NER score is an analytic, differentiable similarity function that rewards spatially equivalent residues but ignores non-equivalent ones. Maximization of the NER score results in accurate superpositions in cases where root mean square deviation (RMSD) minimization fails. Third, the NER function is used in conjunction with traditional dynamic programming to realign the structures based on the proximity of residues in the superposition. Results are presented for a wide range of superposition problems and compared to results from Dali, CE, and VAST. In addition, several structure-structure pairs that show only partial similarity are discussed, and results are compared to those from the LGA, SARF2, and ThreeCa programs., (Copyright 2004 Wiley-Liss, Inc.)

We present a novel approach to protein structure prediction in which fold recognition techniques are combined with ab initio folding methods. Based on the predicted secondary structure, one of two different protocols is followed. For mostly alpha proteins, global optimization and sampling of a statistical energy function is used to generate many low-energy structures; these structures are then screened against a fold library. Any structural matches are then selected for further refinement. For proteins predicted to have significant beta-content, sequence and secondary structure-based alignment is used to identify candidate templates; spatial constraints are then extracted from these templates and used, along with the statistical energy function, in the global sampling and optimization program. Successes and failures of both protocols are discussed., (Copyright 2002 Wiley Liss, Inc.)

We report the tertiary structure predictions for 95 proteins ranging in size from 17 to 160 residues starting from known secondary structure. Predictions are obtained from global minimization of an empirical potential function followed by the application of a refined atomic overlap potential. The minimization strategy employed represents a variant of the Monte Carlo plus minimization scheme of Li and Scheraga applied to a reduced model of the protein chain. For all of the cases except beta-proteins larger than 75 residues, a native-like structure, usually 4-6 A root-mean-square deviation from the native, is located. For beta-proteins larger than 75 residues, the energy gap between native-like structures and the lowest energy structures produced in the simulation is large, so that low RMSD structures are not generated starting from an unfolded state. This is attributed to the lack of an explicit hydrogen bond term in the potential function, which we hypothesize is necessary to stabilize large assemblies of beta-strands., (Copyright 1999 Academic Press.)

We report a new method for predicting protein tertiary structure from sequence and secondary structure information. The predictions result from global optimization of a potential energy function, including van der Waals, hydrophobic, and excluded volume terms. The optimization algorithm, which is based on the alphaBB method developed by Floudas and coworkers (Costas and Floudas, J Chem Phys 1994;100:1247-1261), uses a reduced model of the protein and is implemented in both distance and dihedral angle space, enabling a side-by-side comparison of methodologies. For a set of eight small proteins, representing the three basic types--all alpha, all beta, and mixed alpha/beta--the algorithm locates low-energy native-like structures (less than 6A root mean square deviation from the native coordinates) starting from an unfolded state. Serial and parallel implementations of this methodology are discussed.

We describe new methods for predicting protein tertiary structures to low resolution given the specification of secondary structure and a limited set of long-range NMR distance constraints. The NMR data sets are derived from a realistic protocol involving completely deuterated 15N and 13C-labeled samples. A global optimization method, based upon a modification of the alphaBB (branch and bound) algorithm of Floudas and co-workers, is employed to minimize an objective function combining the NMR distance restraints with a residue-based protein folding potential containing hydrophobicity, excluded volume, and van der Waals interactions. To assess the efficacy of the new methodology, results are compared with benchmark calculations performed via the X-PLOR program of Brünger and co-workers using standard distance geometry/molecular dynamics (DGMD) calculations. Seven mixed alpha/beta proteins are examined, up to a size of 183 residues, which our methods are able to treat with a relatively modest computational effort, considering the size of the conformational space. In all cases, our new approach provides substantial improvement in root-mean-square deviation from the native structure over the DGMD results; in many cases, the DGMD results are qualitatively in error, whereas the new method uniformly produces high quality low-resolution structures. The DGMD structures, for example, are systematically non-compact, which probably results from the lack of a hydrophobic term in the X-PLOR energy function. These results are highly encouraging as to the possibility of developing computational/NMR protocols for accelerating structure determination in larger proteins, where data sets are often underconstrained., (Copyright 1999 Academic Press.)

We describe an improved algorithm for protein structure prediction, assuming that the location of secondary structural elements is known, with particular focus on prediction for proteins containing beta-strands. Hydrogen bonding terms are incorporated into the potential function, supplementing our previously developed residue-residue potential which is based on a combination of database statistics and an excluded volume term. Two small mixed alpha/beta proteins, 1-CTF and BPTI, are studied. In order to obtain native-like structures, it is necessary to allow the beta-strands in BPTI to distort substantially from an ideal geometry, and an automated algorithm to carry this out efficiently is presented. Simulated annealing Monte Carlo methods, which contain a genetic algorithm component as well, are used to produce an ensemble of low-energy structures. For both proteins, a cluster of structures with low RMS deviation from the native structure is generated and the energetic ranking of this cluster is in the top 2 or 3 clusters obtained from simulations. These results are encouraging with regard to the possibility of constructing a robust procedure for tertiary folding which is applicable to beta-strand containing proteins.